Revenue Per Email Sent Calculator
Test a different scenario
Change any scenario value below. Your original calculation stays unchanged.
Scenario calculations use the same formula and v2.5 validation rules as the main calculator. No scenario values are sent to Borkish.
Calculations and What-If scenarios run in your browser. Borkish does not require you to submit these values to calculate the result.
What the Revenue Per Email Sent Calculator measures
This normalizes email revenue across campaigns with different send volumes. Measure list performance, campaign efficiency and customer communication metrics.
The result becomes more useful when every input follows the same definition and reporting period. That keeps comparisons between campaigns, products, customers and time periods meaningful.
When to use this calculator
- Use the Revenue Per Email Sent Calculator to review campaign or list performance using one reporting period.
- Compare email efficiency before changing frequency, targeting or creative.
- Connect communication activity with revenue, retention or customer outcomes.
Formula
Use one currency consistently for every monetary input. The calculator changes the display symbol only; it does not perform foreign-exchange conversion.
How to use this calculator
- Revenue Attributed to EmailUse the value from the same reporting period or scenario as your other inputs.
- Emails SentUse the value from the same reporting period or scenario as your other inputs.
- Complete the required inputsThe result updates automatically as the values become valid.
- Compare the resultUse a previous period, target or relevant internal benchmark before making a decision.
Worked example
Using the demonstration values — Revenue Attributed to Email = 20000, Emails Sent = 100000 — the calculator returns $0.20. The example shows how the formula behaves; replace the demonstration data with your own before using the result for planning.
How to interpret the result
This normalizes email revenue across campaigns with different send volumes. These calculators work best with numbers from the same email campaign, CRM report or reporting period.
Check the definition of Revenue Attributed to Email, Emails Sent, the attribution or accounting rules behind those inputs, and any important costs or outcomes that the formula does not include.
Common mistakes to avoid
- Using Revenue Attributed to Email and Emails Sent from different reporting periods or definitions.
- Combining data from different campaigns or list segments.
- Treating opens or clicks as revenue without a clear attribution rule.
Frequently asked questions
What does this calculator do?
Calculate average attributed revenue for each email sent.
Where should I get the input values?
Use your own advertising platform, ecommerce system, accounting report, CRM, analytics platform or forecast — whichever source is authoritative for the metric. Keep all inputs on the same basis and date range.
Is there one good result I should target?
Usually not. A useful target depends on your margins, acquisition model, operating costs, channel, market and business goals. Your own historical performance is often a better starting benchmark than a generic number.
Can I use this for forecasting?
Yes. Enter forecast values to model a scenario, but treat the output as an estimate based on those assumptions rather than a prediction of future performance.
Can I use a different currency?
Yes. Select a display currency and keep every monetary input in that same currency. The calculator does not convert exchange rates.
What to calculate next
This normalizes email revenue across campaigns with different send volumes. A single metric rarely explains the whole decision, so compare this result with the related cost, conversion, margin or growth metrics below before acting on it.
Calculate the percentage of sent emails that bounced.
Calculate return on email marketing investment.
Calculate email click rate based on delivered messages.
Keep reporting periods and metric definitions consistent when moving between calculators. That makes the comparison more useful than treating each result as a standalone benchmark.